Mongodb Features

Old time series data can also be configured for automatic purging or—for Atlas users—archived out to low-cost storage. Hackolade was specially built to support the data modeling of MongoDB collections, supporting multiple databases as well. Accordingly, as MongoDB has a single master node, it is limited in terms of writing scalability.

If you don’t use indexes, then the database is forced to hold a various amount of documents while sorting. If MongoDB hits the limitation, then the database will return an error or an empty set. On the other hand, if your database has large documents with constant updates and you want good performance on writes, then you may want to consider normalization. Alternatively, Cassandra only has cursor support for the secondary index.

When making a comparison between two database systems, it is usually inferred there are shared similarities as well. Although they do exist, in regards to Cassandra and MongoDB, these similarities are limited. If you are searching for a NoSQL database, you probably came across Cassandra and MongoDB. Still, these two popular NoSQL choices have much less in common than expected. Database Trends and Applications delivers news and analysis on big data, data science, analytics and the world of information management.

Cassandra Vs Mongodb: Similarities

Or in other words, MongoDB environment gives you a server that you can start and then create multiple databases on it using MongoDB. Normalization – is storing data into multiple collections with references between them. For example, storing the persons in a document and the addresses in another document. Normalization defines the data only once making the writes tasks easier. If you want to receive data from multiple collections, you have to perform multiple queries making the reads slower. In the diagram below you can see the difference between the classic way of storing data in Relational Databases and MongoDB.

  • Nowadays there are so many companies that used MongoDB like Facebook, Nokia, eBay, Adobe, Google, etc. to store their large amount of data.
  • To get the best out of MongoDB, you have to understand and follow some basic database design principles.
  • In MongoDB, you can search by field, range query and it also supports regular expression searches.
  • Hackolade dynamically generates the validator script based on model attributes and constraints.
  • Accordingly, as MongoDB has a single master node, it is limited in terms of writing scalability.

Hackolade also supports MongoDB Enterprise security features, with LDAP and Kerberos authentication. MongoDB is a free and open-source cross-platform document-oriented database program. Classified as a NoSQL database program, MongoDB uses JSON-like documents with schemas. The data stored in the MongoDB is in the format of BSON documents. Or in other words, in the backend, the MongoDB server converts the JSON data into a binary form that is known as BSON and this BSON is stored and queried more efficiently. MongoDB is an open-source document-oriented database that is designed to store a large scale of data and also allows you to work with that data very efficiently.

Reasons Customers Turn From Mongodb To Couchbase

Plus, all nodes within a cluster are active – there’s no single, primary node chokepoint that hands-off to “secondary nodes” and slows things down. Closely aligned with time series are the introduction of new analytic “windowing” functions within the aggregation framework. Windowing functions will be familiar to SQL users—they allow functions to operate over a “window” of documents in some ordered dataset. For instance, windowing functions allow you to compare the current value with the average value for the last 24 hours or to calculate a moving average. Along with the relational database, it also supports the JSON document model, which means it responds to the NoSQL queries as well. PostgreSQL is used for many mobile applications and analytical applications.

Finally, many consider MongoDB to have the upper hand when it comes to consistency requirements. Also, you can manually configure Cassandra to meet the consistency standards you set. Cassandra has no aggregation framework and requires external tools like Hadoop, Spark and others.

What’s more, the load characteristic of the application your database needs to support also plays a crucial role. If you are expecting heavy load input, Cassandra, with its multiple master nodes, will give better results. With heavy load output both MongoDB and Cassandra will show good performance. All of Couchbase’s key-value data retrieval and processing operations happen in memory, resulting in sub-millisecond performance.

MongoDB Key Features

It is categorized under the NoSQL database because the storage and retrieval of data in the MongoDB are not in the form of tables. Now a day many companies using MongoDB to create new types of applications, improve performance and availability. A thorough understanding of MongoDB combined with a clear view of what you want to achieve with the database can be the recipe for good database design and best performance. Even though MongoDB is “schemaless”, there are still ways to visualize the collections as diagrams. Being able to view the diagram will have a great impact on how you understand the database and the relations between them.


Even novice users can query the database using Full-Text Search, with geospatial capabilities. The in-memory key-value managed cache delivers millisecond performance without needing a separate caching product. Couchbase easily scales by simply adding necessary nodes one MongoDB vs PostgreSQL at a time, while MongoDB needs to add at least three new nodes at a time in order to introduce a new shard to the cluster, which drives up your total cost of ownership . Meanwhile Couchbase automatically creates shards and rebalances distribution to all available nodes.

MongoDB represents JSON documents in binary-encoded format called BSON behind the scenes. BSON extends the JSON model to provide additional data types, ordered fields, and to be efficient for encoding and decoding within different languages. The MongoDB BSON implementation is lightweight, fast and highly traversable. Still, it is more flexible than relational databases since each row is not required to have the same columns.

MongoDB Key Features

Hackolade was specially built to support the data types and attributes behavior of MongoDB, including the BSON types. Understanding the concepts of normalization and denormalization is a key point in building an efficient database. Following some basic database design principles will help you get the best out of MongoDB.

Long-running queries within a transaction can now extend to five minutes by default or longer if configured. Previously, transactional statements were limited to just one minute. Under the hoods, transaction snapshots are now written to disk storage rather than memory, allowing for larger transaction windows. The unique feature of Redis is that it supports the “Lua script”, due to which it is known as an intelligent cache; so it can be used for high computations. Azure Cosmos DB is also a NoSQL database, which is used to store the data of a website and is released by Microsoft as its name indicates.

The easiest way is to use ERD tools and draw your database from scratch. The Couchbase auto-failover is robust and quick, based on multiple signals of liveness. MongoDB’s failover technology, on the other hand, is slower and limited as it’s based only on heartbeats between replica-set nodes. MongoDB is a database program that provides high performance, high availability, and automatic scaling to… There are a number of factors that impact the performance of these two types of databases.

But first, let’s just have a quick recap on how MongoDB stores data. If you’re ready to move beyond a “general purpose” database and build robust enterprise applications, then you’re ready to try out Couchbase for yourself. The N1QL query language means developers, DBAs, analysts and others with SQL knowledge ramp up fast with “SQL++”. Like others who first explore NoSQL technology, this team began with MongoDB for their microservices applications. As the demand and mission-criticality of these applications grew, the development team switched to Couchbase. In addition, write processing is separated from read and query activities, meaning that writes never interfere with read and query actions.

Integrated Services For Flexible Development & Data Access

BSON is a binary serialization format used to store documents and make remote procedure calls in MongoDB. You are not allowed to store more than 16MB data in the documents. If you’re interested in learning more about N1QL and Couchbase, I encourage you to try it out for yourself with this free online N1QL tutorial. Or, compare N1QL to MongoDB’s query language in this third-party evaluation. Just compare the MongoDB query language with Couchbase N1QL side by side in the image below. The second reason many enterprises switch from MongoDB to Couchbase is because of N1QL, the Couchbase query language.

Unlike the relational databases we know, NoSQL can store large amounts of data without requiring a logical category or schema. MongoDB’s latest marketing/architecture slide gives a hint toward the forward strategy of the company. It emphasizes the document model as the core of the product line, but provides a unified interface across other data models—such as graph, relational, etc.


MongoDB’s time series collections have optimized internal storage to facilitate these workload patterns. In 2009, Salvatore Sanfilippo developed the Redis which is known as a purpose-built database, which means it needs some static memory to store the data because it has no server where its data can be stored. It also has the feature of using the persistent data structure by which the users can perform complex tasks with excellent performance. Fields are key-value pairs in the documents, it is just like columns in the relation database. The value of the fields can be of any BSON data types like double, string, boolean, etc. Another key factor that Couchbase customers love is the multiple built-in services that the platform offers to access and manage data without using additional databases.

This tutorial shows you how to use Docker and an official MongoDB container image to deploy your databases…. When it comes to the schema, you should decide whether you want a flexible database or a stationary one. Data scientists using Python will welcome the PyMongoArrow API, which converts MongoDB query results to python formats popular in machine learning and statistical analysis.

Serverless Atlas

Its queries are limited to single columns and equality comparisons. MongoDB uses queries structured into JSON fragments and does not have any query language support yet. If you or your team is used to SQL, this will be something to get used to. Another distinguishing factor is whether you need a database that has query language support. Serverless Atlas provides on-demand access to Atlas cloud database services. Rather than configuring a cluster to a fixed size, Atlas will provide truly dynamic resources to your application requests—scaling CPU and Memory as required to deal with the workload and discarding those resources when the request completes.

MongoDB Key Features

Similarly, MongoDB is very much easy to use as compared to Redis, likewise, if you are going to handle a lot of queries, MongoDB will be better than Redis because of its simple JSON document model. If you are going to manage hundreds of documents then it will be better to use MongoDB as it contains a high processing speed than PostgreSQL, because it can use a horizontal scaling approach. On the other hand, if you have to establish the relationship between the tables, it will be better to use the PostgreSQL database. The connection is established using a connection string including address and port , and authentication using username/password if applicable. X.409 SSL encryption can be specified, and SSH tunneling to a Cloud instance is supported as well.

However, MongoDB points out that in order to achieve a high frequency of releases, they need to reduce the amount of testing that must be performed on all possible hardware platforms. Furthermore, these rapid release are available for evaluation and development purposes—I’d expect them to be widely deployed in non-critical contexts. In the initial release, time series collections cannot be sharded or manipulated within transactions—I expect those limitations to be removed in upcoming releases. Since version 3.2, MongoDB provides the capability to validate documents during updates and insertions. Validation rules are specified on a per-collection basis using the validator option, which takes a document that specifies the validation rules or expressions. Hackolade dynamically generates the validator script based on model attributes and constraints.

Creating virtual foreign keys for MongoDB can be also very helpful for data visualization. One of Couchbase’s key advantages is exceptional throughput and low latency at scale. The MEAN stack is an open-source JavaScript framework used for developing robust web applications…

Who Are Mongodbs Major Competitors? Amazon Dynamodb, Microsoft Azure Cosmos Db , Couchbase, Postgresql, Redis, Cassandra

Since traditional databases weren’t able to handle a lot of unstructured data in real-time, NoSQL databases took up the challenge by scaling horizontally. It’s worth noting that while MongoDB Atlas remains a cornerstone of MongoDB’s revenue strategy, the company seems to have resisted the temptation to make these new features Atlas-only. To be sure, there are many features added to Atlas, but generally, these are features that only make sense within the fully managed Database as a Service paradigm.

It also provides official driver support for all the popular languages like C, C++, C#, and .Net, Go, Java, Node.js, Perl, PHP, Python, Motor, Ruby, Scala, Swift, Mongoid. So, that you can create an application using any of these languages. Nowadays there are so many companies that used MongoDB like Facebook, Nokia, eBay, Adobe, Google, etc. to store their large amount of data. Initially created by developers from Facebook, Cassandra is now under the ownership of the Apache project and part of its open-source community. On the other hand, MongoDB is one of the most popular database management systems in the world with a strong community of MongoDB developers.

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